FT Cboe Correlations

FJUL Etf

USD 47.61 1.03 2.12%

The current 90-days correlation between FT Cboe Vest and FT Cboe Vest is 0.97 (i.e., Almost no diversification). A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as FT Cboe moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if FT Cboe Vest moves in either direction, the perfectly negatively correlated security will move in the opposite direction.

FT Cboe Correlation With Market

Poor diversification

The correlation between FT Cboe Vest and DJI is 0.63 (i.e., Poor diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding FT Cboe Vest and DJI in the same portfolio, assuming nothing else is changed.

Check out Investing Opportunities to better understand how to build diversified portfolios, which includes a position in FT Cboe Vest. Also, note that the market value of any etf could be closely tied with the direction of predictive economic indicators such as signals in employment.

Moving together with FJUL Etf

0.99	BUFR	First Trust Cboe	Pair Corr
0.96	BUFD	FT Cboe Vest	Pair Corr
0.99	PSEP	Innovator SP 500	Pair Corr
0.78	PJAN	Innovator SP 500	Pair Corr
0.99	PJUL	Innovator SP 500	Pair Corr
0.98	PAUG	Innovator Equity Power	Pair Corr
0.99	DNOV	FT Cboe Vest	Pair Corr
0.78	PMAY	Innovator SP 500	Pair Corr
0.94	PJUN	Innovator SP 500	Pair Corr
0.64	WMT	Walmart	Pair Corr
0.7	JPM	JPMorgan Chase	Pair Corr
0.75	AXP	American Express	Pair Corr

Moving against FJUL Etf

0.31	AMPD	Tidal Trust II	Pair Corr
0.46	MRK	Merck Company Aggressive Push	Pair Corr

Related Correlations Analysis

	META	MSFT	UBER	F	T	A	CRM	JPM	MRK	XOM
META		-0.46	0.68	-0.53	0.66	0.2	-0.15	0.89	-0.83	0.0	META
MSFT	-0.46		-0.68	0.54	-0.72	0.45	0.83	-0.43	0.62	0.05	MSFT
UBER	0.68	-0.68		-0.35	0.79	-0.2	-0.59	0.7	-0.8	0.35	UBER
F	-0.53	0.54	-0.35		-0.35	0.25	0.43	-0.39	0.66	0.55	F
T	0.66	-0.72	0.79	-0.35		-0.41	-0.58	0.56	-0.73	0.14	T
A	0.2	0.45	-0.2	0.25	-0.41		0.55	0.39	0.14	0.13	A
CRM	-0.15	0.83	-0.59	0.43	-0.58	0.55		-0.18	0.44	0.04	CRM
JPM	0.89	-0.43	0.7	-0.39	0.56	0.39	-0.18		-0.77	0.14	JPM
MRK	-0.83	0.62	-0.8	0.66	-0.73	0.14	0.44	-0.77		0.01	MRK
XOM	0.0	0.05	0.35	0.55	0.14	0.13	0.04	0.14	0.01		XOM
	META	MSFT	UBER	F	T	A	CRM	JPM	MRK	XOM

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Correlation Matchups

Over a given time period, the two securities move together when the Correlation Coefficient is positive. Conversely, the two assets move in opposite directions when the Correlation Coefficient is negative. Determining your positions' relationship to each other is valuable for analyzing and projecting your portfolio's future expected return and risk.

High positive correlations

JPM	+ 0.89	META
CRM	+ 0.83	MSFT
T	+ 0.79	UBER
JPM	+ 0.7	UBER
UBER	+ 0.68	META
T	+ 0.66	META

High negative correlations

MRK	- 0.83	META
MRK	- 0.8	UBER
MRK	- 0.77	JPM
MRK	- 0.73	T
T	- 0.72	MSFT
UBER	- 0.68	MSFT

FT Cboe Competition Risk-Adjusted Indicators

There is a big difference between FJUL Etf performing well and FT Cboe ETF doing well as a business compared to the competition. There are so many exceptions to the norm that investors cannot definitively determine what's good or bad unless they analyze FT Cboe's multiple risk-adjusted performance indicators across the competitive landscape. These indicators are quantitative in nature and help investors forecast volatility and risk-adjusted expected returns across various positions.

	Mean Deviation	Jensen Alpha	Sortino Ratio	Treynor Ratio	Semi Deviation	Expected Shortfall	Potential Upside	Value @Risk	Maximum Drawdown
META	1.49	0.20	0.11	0.18	1.74	(1.47)	3.22	(2.31)	8.58
MSFT	1.06	(0.07)	0.00	(0.23)	0.00	0.00	2.56	(2.14)	10.31
UBER	1.95	0.12	0.06	1.22	2.80	(1.97)	4.72	(3.13)	12.28
F	1.42	(0.04)	0.00	(0.11)	0.00	0.00	2.71	(2.89)	10.14
T	1.05	0.31	0.21	0.42	1.34	(1.17)	2.10	(1.97)	11.66
A	1.10	(0.07)	0.00	(0.18)	0.00	0.00	2.80	(2.53)	9.03
CRM	1.44	(0.15)	0.00	(0.26)	0.00	0.00	2.21	(2.95)	15.92
JPM	1.01	0.03	0.00	(0.04)	0.00	0.00	1.97	(1.98)	6.85
MRK	1.22	(0.09)	0.00	(18.91)	0.00	0.00	2.15	(2.24)	11.57
XOM	0.98	(0.07)	0.00	(0.23)	0.00	0.00	1.92	(2.50)	5.89

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